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Chaîne source @OnePlusGuide · Post #2740 · 22 août

🔻IL GLOSSARIO DEL MODDING🔻 #ONEPLUSNORD#MODDING Nei nostri gruppi abbiamo notato che c'è un numero abbastanza importante di utenti che vorrebbe iniziare a fare i primi passi nel mondo del Modding ma non sa da dove partire. Noi di OnePlus IT Staff abbiamo pensato di fornirvi quello che noi amiamo chiamare "il Glossario del Modding" che racchiude, in un elenco con annessa descrizione, tutti i termini e/o concetti che sono la base del Modding, in maniera tale da fornirvi la formazione di base per poter capire come il Modding può migliorare l'esperienza d'uso del vostro dispositivo. N.B. Il post sarà in continuo aggiornamento da qui in avanti, perciò assicuratevi di dargli un'occhiata ogni tanto! 🔸 Il Glossario del Modding Pit — Il nostro canale 👉🏻@oneplusguide I nostri gruppi 👉🏻@oneplusitcommunity

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Repositorio data science

@repo_science · Post #3688 · 03/11/2023 12:00

#ML 😎 FREE RESOURCES TO LEARN MACHINE LEARNING Intro to ML by MIT Free Course Machine Learning for Everyone FREE BOOK ML Crash Course by Google Advanced Machine Learning with Python Github Practical Machine Learning Tools and Techniques Free Book Python Machine Learning for beginners ----- Main channel: @repo_science Coupons: @freecoupons_reposcience -----

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Repositorio data science

@repo_science · Post #3447 · 17/07/2023 15:14

#ML 🧠 Machine Learning Expert El aprendizaje automático es un vasto campo con muchos conceptos clave que conocer. Nuestro curso intensivo cubre todos los componentes básicos que necesita para sumergirse en el aprendizaje automático del mundo real. ✍️Ryan Doan | Ex-Amazon ML Infrastructure Engineer 🌐En 📆2022 🔗Link ----- Main channel:@repo_science Coupons:@freecoupons_reposcience -----

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Am Neumarkt 😱

@amneumarkt · Post #617 · 25/08/2024 14:03

#ml What’s Really Going On in Machine Learning? Some Minimal Models—Stephen Wolfram Writings https://writings.stephenwolfram.com/2024/08/whats-really-going-on-in-machine-learning-some-minimal-models/

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Am Neumarkt 😱

@amneumarkt · Post #607 · 30/07/2024 06:20

#ml Meta's second version of segment anything. https://github.com/facebookresearch/segment-anything-2 They have a nice demo: https://sam2.metademolab.com/

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Am Neumarkt 😱

@amneumarkt · Post #596 · 07/07/2024 20:53

#ml I was searching for a tool to visualize computational graphs and ran into this preprint. The hierarchical visualization idea is quite nice. https://arxiv.org/abs/2212.10774

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Am Neumarkt 😱

@amneumarkt · Post #595 · 06/07/2024 22:02

#ml Schmidhuber J. Deep Learning: Our Miraculous Year 1990-1991. In: arXiv.org [Internet]. 12 May 2020 [cited 7 Jul 2024]. Available: https://arxiv.org/abs/2005.05744

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Am Neumarkt 😱

@amneumarkt · Post #538 · 16/02/2024 11:21

#ml Like a dictionary Kunc, Vladim’ir, and Jivr’i Kl’ema. 2024. “Three Decades of Activations: A Comprehensive Survey of 400 Activation Functions for Neural Networks.” arXiv [Cs.LG], February. http://arxiv.org/abs/2402.09092.

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Am Neumarkt 😱

@amneumarkt · Post #532 · 09/02/2024 05:35

#ml I got interested in satellite data last year and played with it a bit. It's fantastic. The spatiotemporal nature of it brings up a lot of interesting questions. Then I saw this paper today: Rolf, Esther, Konstantin Klemmer, Caleb Robinson, and Hannah Kerner. 2024. “Mission Critical -- Satellite Data Is a Distinct Modality in Machine Learning.” arXiv [Cs.LG], February. http://arxiv.org/abs/2402.01444.

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Am Neumarkt 😱

@amneumarkt · Post #531 · 05/02/2024 10:57

#ml Jelassi S, Brandfonbrener D, Kakade SM, Malach E. Repeat after me: Transformers are better than state space models at copying. arXiv [cs.LG]. 2024. Available: http://arxiv.org/abs/2402.01032 Not surprising at all when you have direct access to a long context. But hey, look at this title.

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